Compression allows more economic encodings of data (e.g., fewer bits) than an original representation. Accordingly, compression may reduce both storage and communication requirements. Data can be compressed, for example, via the use of software and/or hardware. Software compression may afford a greater compression ratio than hardware compression, but may require significant computation resources and/or power use.
Existing hardware compression techniques may be overly conservative for large regular data arrays. For example, a number of hardware compression techniques target generic data types and frequent update(s) to data. When compressing generic data, existing hardware compression techniques may be limited to the use of either complex codes or simpler, less effective, codes. Moreover, frequent updates to data may cause a number of complications for existing hardware compression techniques associated with, for example, page mapping, fragmentation, and/or relocation.